TSP 遗传算法

clc,clear;
sj0 = load(‘sj.txt‘);
x = sj0(:,1:2:8); x = x(:);
y = sj0(:,2:2:8); y = y(:);
sj = [x,y];d1 = [70,40];
sj = [d1;sj;d1]; sj = sj*pi/180;
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d = zeros(102);
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for i  = 1:101
    for j = i+1:102
        d(i,j) = 6370*acos(cos(sj(i,1)-sj(j,1))*cos(sj(i,2))*cos(sj(j,2))+sin(sj(i,2))*sin(sj(j,2)));
    end
end
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d = d + d‘;
% w 为种群数,g为进化的代数
w = 50;
g = 100;
rand(‘state‘,sum(clock));
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% 改良圈算法选取初始种群
for k=1:w  %通过改良圈算法选取初始种群
    c=randperm(100); %产生1，...，100的一个全排列  
    c1=[1,c+1,102]; %生成初始解
    for t=1:102 %该层循环是修改圈
        flag=0; %修改圈退出标志
        for m=1:100
            for n=m+2:101
                if d(c1(m),c1(n))+d(c1(m+1),c1(n+1))<d(c1(m),c1(m+1))+d(c1(n),c1(n+1))
                    c1(m+1:n)=c1(n:-1:m+1);  flag=1; %修改圈
                end
            end
        end
        if flag==0
            J(k,c1)=1:102; break %记录下较好的解并退出当前层循环
        end
   end
end
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% 染色体编码
J(:,1) = 0;
J = J/102;
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% 100次进化
for k = 1:g
    A = J;
    c = randperm(w);
    for i = 1:2:w                       % 基因重组
        F = 2 + floor(100*rand(1));     % 产生交叉操作的染色体对
        tmp = A(c(i),[F:102]);
        A(c(i),[F:102]) = A(c(i+1),[F:102]);
        A(c(i+1),F:102) = tmp;
    end
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    % 变异
    by = [];
    while ~isempty(by)      % 变异的个体数也是随机的
        by =find(rand(1,w)<0.1);
    end
    
    B = A(by,:);        % 变异染色体
    for j = 1:length(by)
        bw = sort(2+floor(100*rand(1,3)));      % 产生变异操作的3个地址
        B(j,:) = B(j,[1:bw(1),bw(2)+1:bw(3),bw(1):bw(2),bw(3)+1:102]);
        
    end
    
    G=[J;A;B];       % 父代和子代
    % 基因翻译为解空间,把染色体翻译成1,...,102的序列ind1
    [SG,ind1] = sort(G,2);
    num = size(G,1);        % 父子种群的总个体数
    long = zeros(1,num);
    
    % 每一个体的优劣
    for j = 1:num
        for i = 1:101
            long(j) = long(j)+d(ind1(j,i),ind1(j,i+1));
        end
    end
    
    [slong,ind2] = sort(long);
    J = G(ind2(1:w),:);
end
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path = ind1(ind2(1),:);
flong = slong(1);
xx = sj(path,1);
yy = sj(path,2);
plot(xx,yy,‘-o‘);